Agentforce Grid: No code tool for testing Salesforce AI workflows.

By Uttam Prabhu

Introduction & What is Agentforce Grid?

Definition: Agentforce Grid is an AI-native spreadsheet workspace built directly inside Salesforce. It lets users combine CRM data, AI prompts, actions, and autonomous agents into a single, familiar spreadsheet view to prototype, test, and scale automated workflows in bulk without writing code.
Key FeaturesBulk execution: Process hundreds or thousands of rows independently in parallel with a single click.Visual debugging: Inspect individual cells to view raw API responses, safety scores, and agent session traces.No-code design: Build and validate complex multi-turn logic using a familiar spreadsheet layout rather than complex flows or Apex code.

Business Use Case & Value

Business Value Statement: This workflow automatically aggregates record snapshots and field modification histories (LeadHistory) for high-revenue leads, using AI to generate a 2-bullet executive briefing that helps sales reps track past prospect behavior and personalize outreach faster.

Step-by-Step Implementation Guide

1. Prerequisites

Create a custom field on the Lead object: AI_Executive_Summary__c (Type: Rich Text Area).
Lead History Summarization: This is a prompt template that analyzes current lead data and field history to produce a concise two-bullet executive summary highlighting engagement velocity, behavioral trends, and a personalized next-step recommendation for the sales rep.
- Input 1: Lead Record Id
- Input 2: Formatted text of leads behaviour based on Lead History data.

Now we will be building a grid to figure out how well the prompt template works across different leads and their diverse behaviour.

2. Creating the Grid Workspace

Search for Agentforce Grid in the App Launcher.
Click Create Grid > Create from Scratch.
Name the workspace: VIP Lead Behaviour Analysis.

3. Configuring the Grid Columns

1.Target High-Value Leads: Salesforce Query.

Add Column 1: Object = Lead, Filter: AnnualRevenue > 1M.

2.Retrieve Lead History: Apex Action.

Add Column 2: Pass Lead.Id as input to an Invocable Apex Action that returns a concatenated string of LeadHistory (field modifications, status changes, and past behavior).

3.Run AI Summarization: Prompt Template (LLM).

Add Column 3: Pass the Lead details and formatted history string into a Prompt Template configured to produce a concise 2-bullet point behavioral briefing.

4.Preview Output: Data Display.

Add Column 4: Display the prompt template’s generated AI summary response directly in the grid cell for review.

5.Write Back to CRM: Record Update.

Add Column 5: Map and update the summary response directly into the AI_Executive_Summary__c custom field on the Lead record.

Execution, Verification & Monitoring

1. Bulk Execution

Select all rows in the grid and click Run Rows.
Monitor the pipeline as columns execute sequentially until the last column displays the Record Updated status.
Verify by navigating to any target Lead record in Salesforce to view the populated AI_Executive_Summary__c field.

2. Monitoring Credit Usage & Platform Features

Top-Right Credit Score Indicator: Track overall credit consumption in real time at the top right of the screen while processing rows.

Column-Level Credit Transparency: Inspect individual column metrics to see exactly how many credits were consumed by each action.

Importing & Exporting Worksheets: Export your configured Grid as a CSV file for offline auditing or import existing worksheets to quickly bootstrap new bulk processing pipelines.